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Proceedings Paper

Robust scene text detection based on color consistency
Author(s): Yang Zheng; Heping Liu; Jie Liu; Qing Li; Gen Li
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Paper Abstract

The whole process of text detection in scene images always contain three steps: character candidate detection, false character candidate removal, words extraction. However some errors appear in each step and influence the performance of text detection. According to the disadvantages of each step, we propose the compensation methods to solve these problems. Firstly, a filter based on color of stroke named Stroke Color Transform is used to ensure the integrality of characters and remove some false character candidates. Secondly, a classifier is trained based on gradient features is adopted to remove false character candidates. Thirdly, an extractor based on color of consecutive character named Character Color Transform is employed to extract undetected characters. The proposed technique is test on the two public datasets i.e. ICDAR2011 dataset, ICDAR2013 dataset, the experimental results show that our approach outperforms the state-of-the-art methods.

Paper Details

Date Published: 29 August 2016
PDF: 7 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100334Q (29 August 2016); doi: 10.1117/12.2244860
Show Author Affiliations
Yang Zheng, Univ. of Science and Technology Beijing (China)
Heping Liu, Univ. of Science and Technology Beijing (China)
Jie Liu, Institute of Automation (China)
Qing Li, Univ. of Science and Technology Beijing (China)
Gen Li, Institute of Automation (China)

Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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